In this article, I am going to lay out the case that the biggest challenge to supply chains is data interoperability. In fact, I’ll be so bold as to call this massive and continuing failure of data interoperability, a supply chain nightmare!  Just think about it. The key function of any supply chain is to get the right product to the right place at the right time. To do this paramount supply chain function, you need to have data that is accurate, complete, and timely. So, it is impossible for supply chains to work well when there is a lack of data interoperability between different systems and partners.

However, it is not time to give up hope. In this article, I’ll provide you a description of what supply chain data interoperability is and identify for you its many benefits. What’s more, I’ll describe relatable examples of what happens when a supply chain lacks data interoperability. Lastly, I’ll give you 7 examples of solutions that can go a long way in improving data interoperability in your supply chain. So, let’s unlock innovation in our supply chains! 

“data interoperability is key for getting the right information to the right person at the right time”

What Is Data Interoperability And How Is It Important To Supply Chains?

Basically, data interoperability for logistics refers to the seamless exchange of information between different systems and platforms within a supply chain. Here is a basic definition for data interoperability:

“… the ability to access and process data from multiple sources without losing meaning and then integrate that data for mapping, visualization, and other forms of representation and analysis.”

Global Partnership For Sustainable Development Data

Two Levels Of Data Interoperability

Further, there are two parts or stages to data interoperability. These are:

“Data-level Interoperability: Data-level or syntactic interoperability enables data to be shared across applications and platforms.

Semantic-Level Interoperability: This type of interoperability allows the data to be interpreted correctly…”

AIMultiple

Now, it is important for business leaders to know that there are two parts to data interoperability. The key thing to understand is that the first level, data-level interoperability, just amounts to data transfer, and nothing else. Thus, this means that the “consuming” system can access and store the data from a source system. However, this system does not know how to extract meaning out of the data and turn the data into something actionable. Indeed, this is where the second step, semantic-level interoperability, comes in. This interoperability step is key to turn the data into information that supply chains can use.

Indeed, every supply chain organization needs data interoperability to succeed and stay competitive. So, even if a supply chain has just a few systems and supply chain partners it still needs data interoperability. Positively, data interoperability is the key for getting the right information to the right person at the right time. Moreover, interoperability allows data to flow smoothly between various software applications, systems, and devices. Thus, it enables the efficient integration of processes across the entire distribution network. For more discussion on shipment status interoperability and a possible solution, an intelligent tracking data framework, see my article, The Way To Better Supply Chain Analytics: Overcome Data Interoperability With Intelligent Tracking Status.

“And what happens when we want to exchange more than ‘selected, critical data’? The old mantra about the ‘right data, right person, right time’.”

Heather Leslie

The Interoperability Benefits For Supply Chain Excellence And Innovation.

Successfully resolving data interoperability issues within supply chains has far-reaching implications for innovation potential. Indeed, it opens the door for advanced technologies like Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT) to gain traction more effectively. Positively, these technologies can play an integral role in refining operational efficiency, cost optimization, risk mitigation, and overall business agility. Unlocking supply chain innovation truly begins with overcoming the data interoperability nightmare that plagues many industries today. Here are just a sampling of the many benefits of achieving data interoperability between your various supply chain systems.

Benefits Of Supply Chain Data Interoperability

It is absolutely amazing the benefits that a supply chain can achieve with data interoperability. The bottom line is supply chain data interoperability enables supply chain staff to take action with quality supply chain data that is highly accurate, complete, and timely. Indeed, data interoperability enables the right data to get to the right person at the right time. This results in supply chain excellence and enables innovation to occur.

For more information on the benefits of data interoperability, see Tokenex’s What Is Interoperability and Why Is It Important?

Why Is Data Interoperability Such A Nightmare For Supply Chains?

Achieving Logistics Interoperability: The Best Way to Breakthrough The Tangle Of Dumb Data Integrations

Data interoperability poses numerous challenges particularly for supply chains because of the diverse range of technologies, hardware, and software platforms used by different stakeholders. Few industries have to deal with so many systems, numerous stakeholders, and massive amounts of data. Worse, data updates and status in supply chain operations are by their nature fleeting adding even more challenges for decision-makers.  Moreover, integrating these disparate systems is a monstrous task requires considerable time, effort, and resources. 

Moreover, data standards often differ between organizations, making it difficult to establish a common framework for communication. Also, concerns about data privacy and security hinder the establishment of open data exchange channels. Consequently, these complexities turn data interoperability into a nightmare for supply chain managers who are constantly seeking efficient ways to streamline operations and improve services. To list, below are some examples to further detail why supply chain data interoperability is a nightmare.

11 Examples Of Poor Supply Chain Data Interoperability

1. Inconsistent Data Formats.

For example, one system may use CSV files while another uses XML, causing data translation issues. Worse, even if the data format is the same the data is not normalized where each system have a common understanding of the data content.

2. Lack Of Standardized Codes.

For instance, if one company uses UPC codes while another uses EAN codes, it becomes challenging to accurately identify and track products across the supply chain.

3. Limited Data Sharing Capabilities.

In this case, if a supplier’s system does not allow direct integration with a customer’s system, it can lead to delays and errors in data exchange.

4. Manual Data Entry And Reconciliation.

For example, if a warehouse worker needs to manually enter shipment details into multiple systems, it increases the risk of errors and delays.

5. Lack Of Real-Time Visibility.

Poor supply chain data interoperability will result in a lack of real-time visibility into inventory levels, order status, or transportation updates. This will lead to inefficiencies and disruptions in the supply chain. 

6. Incomplete Or Inaccurate Data.

To illustrate, if a supplier fails to update product specifications in their system, it can lead to incorrect information being shared across the supply chain.

7. Non-Standardized Naming Conventions.

For example, if one company refers to a product as “Widget A” while another refers to it as “Product 123”, it can lead to miscommunication and errors.

8. Lack of Data Validation Checks.

For instance, if a system does not validate the accuracy and completeness of incoming data, it can result in the propagation of errors throughout the supply chain.

9. Incompatible Data Integration Tools.

In this case, if one company uses an API-based integration tool while another uses a file-based integration tool, it will hinder seamless data exchange.

10. Proprietary System Lock-In.

Digital Identity In Logistics And What To Know – The Best Security, Scary Risks

For example, a shipping system has a proprietary data interface. Thus, it makes it difficult for a shipper to onboard new parcel carriers because it can’t print shipping labels for any new carriers that are not compatible with the shipping system. 

11. Ineffective Digital Identity Solution.

With any digital system, you have to have an effective digital identity system. Specifically, these systems are used to verify new users, authorize what they can access, and authenticate users when they access systems. The challenge comes in balancing between having secure systems and usability. For more details on digital identity, see my article, Digital Identity In Logistics And What To Know – The Best Security, Scary Risks.

“Interoperability enables us to seamlessly move data, and more importantly insight, between various systems.”

Amy Waldron, Google Cloud

8 Solutions To Achieve Better Supply Chain Data Interoperability And Unlock Innovation.

There are many solutions available to address the challenges of data interoperability in supply chains. However, it is a challenge for many businesses on where to start. First, there is the dynamic nature of supply chains coupled with the staggering amount of technology solutions out there. Additionally, many supply chains are already chained to legacy systems that have created data silos and can contain many partial copies of the same data. Worse, this data is inaccurate, incomplete, and out-of-date. Well, welcome to modern supply chains! 

The good news is that many of your competitors are in this same data interoperability nightmare. So, the answer is not to do nothing! Indeed, it’s time for you to get more data savvy and focus on taking steps, some big and some small, to improve your supply chain’s data interoperability. To detail, below are eight solutions to improve your data interoperability. 

8 Data Interoperability Solutions for Supply Chains

1. Leverage Standardized Data Formats for Increased Data Interoperability
2. Take Advantage Of Data Sharing Platforms That Are Independent Of Software
3. Implement Data Integration Interfaces Like Application Programming Interfaces (APIs)
4. Make Use of Automation Such As Robotic Process Automation (RPA) And AI to Digitize Processes
5. Take Advantage Of Partner Relationship Management Platforms to Increase Data Interoperability
6. Employ Cloud-Based Solutions for Improved Data Interoperability
7. Leverage A High-Tech 3rd Party Logistics (3PL) Provider To Digitize Your Supply Chain
8. Use Computer Vision AI to Exchange Image-based Supply Chain Transactions to Streamline Data Interoperability

For more details and examples, see my article, Data Interoperability For Supply Chains: The Best Ways To Unlock Your Digital Assets And Empower Innovation.

For more articles from Supply Chain Tech Insights, see latest posts on supply chains, information technology, and data.